LIDAR-based wind speed modelling and control system design

Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone

Review of LIDAR-assisted Control for Offshore Wind Turbine Applications

This is the final version. Available on open access from IOP Publishing via the DOI in this recordEERA DeepWind Offshore Wind R&D Conference 19 - 21 January 2022, Trondheim, NorwayNacelle-mounted, forward-facing Light Detection and Ranging (LIDAR) technology is able to provide knowledge of the incoming wind so that wind turbines can prepare in advance, through feedforward control. LIDAR can aid in improving wind turbine performance across the full operating range, assisting with torque control in below rated wind speeds, pitch control in above rated wind speeds and yaw control for correctly aligning the turbine rotor with the incoming wind direction. The motivations are for decreasing structural loads, resulting in reduced maintenance and extended lifetimes of turbines and their components, and increasing power capture, both of which can lead to reductions in the levelised cost of energy. This paper provides a review of control strategies that have been employed for LIDAR-assisted turbine control. This paper reviews the computational and practical studies that have been performed for both bottom-fixed and floating turbines and the journey that the field has undertaken since its conceptualisation. Detail is provided of the key differences between fixed and floating offshore turbine dynamics. The paper concludes with guidance for future work within the field, with a focus on floating turbines, as the extent of the literature is scarce when compared to bottom-fixed. Suggestions are offered for how the future studies can better account for the current and future industry landscape. Opportunities for testing of LIDAR-assisted floating turbine control in the field, its benefits for floating substructure design, and the steps needed to be taken to ensure its increased utilisation on industrial projects are also discussed.Engineering and Physical Sciences Research Council (EPSRC)Natural Environment Research Council (NERC

LIDAR-assisted wind turbine gain scheduling control for load reduction

A gain-scheduled feedforward controller employing pseudo-LIDAR wind measurement is designed to augment the baseline feedback controller for wind turbine load reduction during above rated operation. The feedforward controller is firstly designed based on a linearised wind turbine model at one specific wind speed, then expanded for full above rated operational envelope with gain scheduling. The wind evolution model is established using the pseudo-LIDAR measurement data which is generated from Bladed using a designed sampling strategy. The combined feedforward and baseline control system is simulated on a 5MW industrial wind turbine model developed at Strathclyde University. Simulation results demonstrate that the gain scheduling feedforward control strategy can improve the rotor and tower load reduction performance for large wind turbines

Pseudo-LIDAR data analysis and feed-forward wind turbine control design

To investigate potential improvement in wind turbine control employing LIDAR measurement, pseudo-LIDAR wind speed data is produced with Bladed using a designed sampling strategy, and assessed with preliminary frequency-domain analysis. A model-inverse feed-forward controller is adapted to combine with feedback control so as to enhance pitch control performance at high wind speed. This controller is applied to an industrial-scale 5MW wind turbine model and the control performance is compared with a baseline feedback controller. Simulation study demonstrates that the combined feed-forward/feedback control scheme has improvements in reducing pitch angle variation and reduction of load relevant metrics

Blade root moment sensor failure detection based on multibeam LIDAR for fault-tolerant individual pitch control of wind turbines

Detection of blade root moment sensor failures is an important problem for fault-tolerant individual pitch control, which plays a key role in reduction of uneven blade loads of large wind turbines. A new method for detection of blade root moment sensor failures which is based on variations induced by a vertical wind shear is described in this paper. The detection is associated with monitoring of statistical properties of the difference between amplitudes of the first harmonic of the blade load, which is calculated in two different ways. The first method is based on processing of the load sensor signal, which contains a number of harmonics. The first harmonic is recovered via least squares estimation of the blade load signal with harmonic regressor and strictly diagonally dominant (SDD) information matrix. The second method is a model-based method of estimation of the first harmonic, which relies on the blade load model and upwind speed measurements provided by multibeam Light Detection and Ranging (LIDAR). This is a new application for future LIDAR-enabled wind turbine technologies. Moreover, adaptation of the load model in a uniform wind field is proposed. This adaptation improves accuracy of the load estimation and hence the performance of the blade load sensor failure detection method

On Using Wind Speed Preview to Reduce Wind Turbine Tower Oscillations

We investigate the potential of using previewed wind speed measurements for damping wind turbine fore-aft tower oscillations. Using recent results on continuous-time H2 preview control, we develop a numerically efficient framework for the feedforward controller synthesis. One of the major benefits of the proposed framework is that it allows us to account for measurement distortion. This results in a controller that is tailored to the quality of the previewed data. A simple yet meaningful parametric model of the measurement distortion is proposed and used to analyze the effects of distortion characteristics on the achievable performance and on the required length of preview. We demonstrate the importance of accounting for the distortion in the controller synthesis and quantify the potential benefits of using previewed information by means of simulations based on real-world turbine data

An overview of proactive wind turbine control

Recent achievements in the proactive turbine control, based on the upwind speed measurements, are described in a unified framework (as an extension of the tutorial [1]), that in turn represents a systematic view of the control activity carried out within the Swedish Wind Power Technology Center (SWPTC). A new turbine control problem statement with constraints on blade loads is reviewed. This problem statement allows the design of a new class of simultaneous speed and pitch control strategies based on the preview measurements and look-ahead calculations. A generation of a piecewise constant desired pitch angle profile which is calculated using the turbine load prediction is reviewed in this article as one of the most promising approaches. This in turn allows the reduction of the pitch actuation and the design of the collective pitch control strategy with the maximum possible actuation rate. Two turbine speed control strategies based on one-mass and two-mass models of the drivetrain are also described in this article. The strategies are compared to the existing drivetrain controller. Moreover, postprocessing technique that can be used for estimation of the turbine parameters with improved performance is also discussed. Postprocessing-based estimation of the turbine inertia moment is given as an example. All the results are illustrated by simulations with a wind speed record from the H\uf6n\uf6 turbine, located outside of Gothenburg, Sweden. Recent achievements in the proactive turbine control, based on the upwind speed measurements are described in a unified framework that in turn represents a systematic view of the control activity carried out within the Swedish Wind Power Technology Center (SWPTC)